Prediction and imitation of other's motions by reusing own forward-inverse model in robots

Tetsuya Ogata, Ryunosuke Yokoya, Jun Tani, Kazunori Komatani, Hiroshi G. Okuno

研究成果: Conference contribution

7 引用 (Scopus)

抜粋

This paper proposes a model that enables a robot to predict and imitate the motions of another by reusing its body forward-inverse model. Our model includes three approaches: (i) projection of a self-forward model for predicting phenomena in the external environment (other individuals), (ii) "triadic relation" that is mediation by a physical object between self and others, (iii) introduction of infant imitation by a parent. The Recurrent Neural Network with Parametric Bias (RNNPB) model is used as the robot's self forward-inverse model. A group of hierarchical neural networks are attached to the RNNPB model as "conversion modules". Experiments demonstrated that a robot with our model could imitate a human's motions by translating the viewpoint. It could also discriminate known/unknown motions appropriately, and associate whole motion dynamics from only one motion snap image.

元の言語English
ホスト出版物のタイトル2009 IEEE International Conference on Robotics and Automation, ICRA '09
ページ4144-4149
ページ数6
DOI
出版物ステータスPublished - 2009 11 2
外部発表Yes
イベント2009 IEEE International Conference on Robotics and Automation, ICRA '09 - Kobe, Japan
継続期間: 2009 5 122009 5 17

出版物シリーズ

名前Proceedings - IEEE International Conference on Robotics and Automation
ISSN(印刷物)1050-4729

Conference

Conference2009 IEEE International Conference on Robotics and Automation, ICRA '09
Japan
Kobe
期間09/5/1209/5/17

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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  • これを引用

    Ogata, T., Yokoya, R., Tani, J., Komatani, K., & Okuno, H. G. (2009). Prediction and imitation of other's motions by reusing own forward-inverse model in robots. : 2009 IEEE International Conference on Robotics and Automation, ICRA '09 (pp. 4144-4149). [5152363] (Proceedings - IEEE International Conference on Robotics and Automation). https://doi.org/10.1109/ROBOT.2009.5152363